DocumentCode
3513561
Title
HRR Signature Classification using Syntactic Pattern Recognition
Author
Turnbaugh, Michael A. ; Bauer, Kenneth W., Jr. ; Oxley, Mark E. ; Miller, J.O.
fYear
2008
fDate
1-8 March 2008
Firstpage
1
Lastpage
9
Abstract
An automatic target classification system contains a classifier that maps a vector of real numbered features characteristic to a specific target onto a class label. Other features can be a string of symbols or alphabets that may not involve real numbers at all. There are certain orderings of the symbols in the strings governed by syntax rules, thus, generating a language, (that is, a collection of strings). Thus, a classifier would map a string to a class label. Such a classifier is called a syntactical classifier and varies greatly from its vector space counter part. This paper will give an overview of the construction of a grammar that generates a language then shows how they fit into a syntactical classification system. The performances of two syntactical classification systems with two and ten labels respectively are presented via confusion matrices. Experiments performed on public release DCS database indicate this approach has sufficient power to perform target detection using HRR signatures.
Keywords
computational linguistics; matrix algebra; pattern classification; radar signal processing; radar target recognition; HRR signature classification; SAR; automatic target classification system; confusion matrices; high range resolution signatures; syntactic pattern recognition; syntactical classification system; syntactical classifier; syntax rules; synthetic aperture radar; vector space counter; Biographies; Cities and towns; Counting circuits; Databases; Distributed control; Formal languages; Object detection; Pattern recognition; Prototypes; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace Conference, 2008 IEEE
Conference_Location
Big Sky, MT
ISSN
1095-323X
Print_ISBN
978-1-4244-1487-1
Electronic_ISBN
1095-323X
Type
conf
DOI
10.1109/AERO.2008.4526421
Filename
4526421
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